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factors: Prior experience in developing algorithms for biomedical image processing (especially aligned with the research group's areas) and machine learning/deep learning techniques. Prior knowledge of data
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of the state of the art in machine learning for generation of artificial data; - identify and select the appropriate methods for the study in question; - develop the research capacity through the application
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of the Grant are:; 1) To apply machine learning algorithms for the diagnosis of faults and malfunctions in photovoltaic plants, using data from SCADA systems combined with synthetic data from digital twins (DT
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to study and demonstrate the benefits of the proposed multi-agent Agentic RAG approaches.; 4. REQUIRED PROFILE: Admission requirements: Master's student in Computer Engineering or related field. The awarding
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infrastructures. Minimum requirements: - Knowledge of Software Engineering; - Knowledge of Computer Networks; - Knowledge of Distributed Systems; - Demonstrated experience in a professional context. 5. EVALUATION
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the usability and user experience of the solutions - Prepare activity reports and scientific articles 4. REQUIRED PROFILE: Admission requirements: PhD student, with a completed master's degree The awarding
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SCIENCE Scientific subarea: Informatics Grant duration: 12 months, starting on 2026-02-16 , with the possibility of being renewed for a maximum term of four years, in the cases of students enrolled in a PhD
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.; - Participate in dissemination activities 4. REQUIRED PROFILE: Admission requirements: Master degree in Computer Engineering or related field The awarding of the fellowship is dependent on the applicants
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from Computer Engineering, which are typically addressed in the core curriculum of the Integrated Master's Degree in Computer Engineering or the Master's Degree in Computer Engineering.; 4. REQUIRED